[1] JAVED M A,ZEADALLY S,HAMIDA E B.Data analytics for cooperative intelligent transport systems[J].Vehicular Communications,2019,15:63-72. [2] KUMAR S V,VANAJAKSHI L.Short-term traffic flow prediction using seasonal ARIMA model with limited input data[J].European Transport Research Review,2015,7(3):1-10. [3] CHEN Chenyi,HU Jianming,MANG Qiang,et al.Short-time traffic flow prediction with ARIMA-GARCH model[C]//Proceedings of 2011 IEEE Intelligent Vehicles Symposium.Washington D.C.,USA:IEEE Press,2011:125-136. [4] LI Sha,SUN Lijun.Prediction of traffic retention based on TFPCM and stochastic model[J].Computer Engineering,2019,45(1):29-34.(in Chinese)李莎,孙丽珺.基于TFPCM与随机模型的交通滞留量预测[J].计算机工程,2019,45(1):29-34. [5] ZHAO Jing,SUN Shiliang.High-order Gaussian process dynamical models for traffic flow prediction[J].IEEE Transactions on Intelligent Transportation Systems,2016,17(7):1-6. [6] ZHU Zheng,PENG Bo,XIONG Chefeng,et al.Short-term traffic flow prediction with linear conditional Gaussian Bayesian network[J].Journal of Advanced Transportation,2016,50(6):1111-1123. [7] ZHANG Mingheng,ZHEN Yaobao,HUI Ganglong,et al.Accurate multisteps traffic flow prediction based on SVM[J].Mathematical Problems in Engineering,2013(6):1-8. [8] YU Bin,YANG Zhongzhen.Bus arrival time prediction using support vector machines[J].Intelligent Transportation Systems,2006,10(4):151-158. [9] FENG Xinxin,LING Xianyao,ZHENG Haifeng,et al.Adaptive multi-kernel SVM with spatial-temporal correlation for short-term traffic flow prediction[J].IEEE Transactions on Intelligent Transportation Systems,2018,20(6):2001-2013. [10] LU Yisheng,DUAN Yanjie,KANG Wenwen,et al.Traffic flow prediction with big data:a deep learning approach[J].IEEE Transactions on Intelligent Transportation Systems,2015,16(2):865-873. [11] SHAO H,SOONG B H.Traffic flow prediction with Long Short-Term Memory Networks(LSTMs)[C]//Proceedings of 2016 IEEE Region 10 Conference.Washington D.C.,USA:IEEE Press,2016:123-135. [12] DAI Xingyuan,FU Rui,LIN Yilun,et al.DeepTrend:a deep hierarchical neural network for traffic flow prediction[C]//Proceedings of the 20th International Conference on Intelligent Transportation Systems.Yakahama,Japan:[s.n.],2017:394-406. [13] LI Yuelong,TANG Dehua,JIANG Guiyuan,et al.Short term traffic flow forecasting based on dimension weighted residual LSTM[J].Computer Engineering,2019,45(6):1-5.(in Chinese)李月龙,唐德华,姜桂圆,等.基于维度加权的残差LSTM短期交通流量预测[J].计算机工程,2019,45(6):1-5. [14] ZHANG D,KABUA M R.Combining weather condition data to predict traffic flow:a GRU based deep learning approach[C]//Proceedings of the 15th IEEE International Conference on Dependable,Autonomic and Secure Computing.Washington D.C.,USA:IEEE Press,2017:243-254. [15] FU Rui,ZHANG Zuo,LI Li.Using LSTM and GRU neural network methods for traffic flow prediction[C]//Proceedings of the 31st Youth Academic Annual Conference of Chinese Association of Automation.Washington D.C.,USA:IEEE Press,2016:435-446. [16] FENG Ning,GUO Shengnan,SONG Chao,et al.Multi-component spatial-temporal graph convolution networks for traffic flow forecasting[J].Journal of Software,2019,30(3):759-769.(in Chinese)冯宁,郭晟楠,宋超,等.面向交通流量预测的多组件时空图卷积网络[J].软件学报,2019,30(3):759-769. [17] WU Yuankai,TAN Huachun.Short-term traffic flow forecasting with spatial-temporal correlation in a hybrid deep learning framework[EB/OL].[2019-05-10].https://arxiv.org/abs/1612.01022. [18] LIU Yipeng,ZHENG Haifeng,FENG Xinin,et al.Short-term traffic flow prediction with Conv-LSTM[C]//Proceedings of International Conference on Wireless Communications and Signal Processing.Washington D.C.,USA:IEEE Press,2017:235-248. [19] TAN Huachun,XUAN Xuan,WU Yuankai,et al.A comparison of traffic flow prediction methods based on DBN[C]//Proceedings of the 16th COTA International Conference of Transportation Professionals.Shanghai:[s.n.],2016:273-283. [20] ZHANG Yaying,HUANG Guan.Traffic flow prediction model based on deep belief network and genetic algorithm[J].IET Intelligent Transport Systems,2018,12(6):533-541. |